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Record W2317762899 · doi:10.1097/mpa.0b013e3181f74c23

Comparative Immunohistochemical Study of the Stroma of Serous and Mucinous Cystic Neoplasms

2010· article· en· W2317762899 on OpenAlexaff
Bich Nguyen, Allison Edgecombe, Marcio M. Gomes, Geneviève Soucy, Celia Marginean

Bibliographic record

VenuePancreas · 2010
Typearticle
Languageen
FieldMedicine
TopicPancreatic and Hepatic Oncology Research
Canadian institutionsHôpital Saint-LucCentre Hospitalier de l’Université de MontréalOttawa Hospital
Fundersnot available
KeywordsStromaStromal cellSerous fluidPathologyVimentinPancreasImmunohistochemistryEstrogen receptorProgesterone receptorBiologyMedicineInternal medicineCancerBreast cancer

Abstract

fetched live from OpenAlex

OBJECTIVES: Serous and mucinous cystic neoplasms (SCNs/MCNs) are the most common true cystic neoplasms of the pancreas and occur more frequently in women. The aim of this study was to characterize the stroma of SCNs to compare its phenotype with that of MCNs. METHODS: A total of 12 SCNs and 5 MCNs were analyzed immunohistochemically using the following antisera: progesterone receptor (PR), estrogen receptor (ER), inhibin, CD10, and vimentin. Normal pancreatic tissue (17 cases) and ductal adenocarcinomas of the pancreas (3 cases) were used as controls. RESULTS: Eight of 12 patients with SCNs and all 5 patients with MCNs were women. For SCNs, the stroma was sclerotic and paucicellular and showed focal moderate to strong reactivity for PR. Estrogen receptor, CD10, and inhibin were virtually negative. For MCNs, the stroma was more cellular and ovarianlike and showed a larger number of PR-positive cells with focal expression of ER and inhibin. Vimentin was expressed in all stromal cells in both groups. CONCLUSIONS: Both SCNs and MCNs contain PR-positive stromal cells. In view of the aforementioned clinical and immunophenotypical similarities, we suggest that in SCNs and MCNs, the stromal framework is similar in origin and/or differentiation.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.286
Threshold uncertainty score0.246

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.023
GPT teacher head0.335
Teacher spread0.312 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations2
Published2010
Admission routes1
Has abstractyes

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